p253-pei - Catching the Best Views of Skyline: A Semantic...

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Unformatted text preview: Catching the Best Views of Skyline: A Semantic Approach Based on Decisive Subspaces * Jian Pei 1 Wen Jin 1 Martin Ester 1 Yufei Tao 2 1 Simon Fraser University, Canada, { jpei, wjin, ester } @cs.sfu.ca 2 City University of Hong Kong, Hong Kong, taoyf@cs.cityu.edu.hk Abstract The skyline operator is important for multi- criteria decision making applications. Al- though many recent studies developed effi- cient methods to compute skyline objects in a specific space, the fundamental problem on the semantics of skylines remains open: Why and in which subspaces is (or is not) an ob- ject in the skyline? Practically, users may also be interested in the skylines in any sub- spaces. Then, what is the relationship be- tween the skylines in the subspaces and those in the super-spaces? How can we effectively analyze the subspace skylines? Can we effi- ciently compute skylines in various subspaces? In this paper, we investigate the semantics of skylines, propose the subspace skyline analy- sis, and extend the full-space skyline computa- tion to subspace skyline computation. We in- troduce a novel notion of skyline group which essentially is a group of objects that are coin- cidentally in the skylines of some subspaces. We identify the decisive subspaces that qual- ify skyline groups in the subspace skylines. The new notions concisely capture the seman- tics and the structures of skylines in various subspaces. Multidimensional roll-up and drill- down analysis is introduced. We also develop an efficient algorithm, Skyey , to compute the * The research of Jian Pei is supported in part by NSERC Grant 312194-05 and NSF Grant IIS-0308001. The research of Yufei Tao is supported in part by Grant CityU 1163/04E from the RGC of HKSAR. All opinions, findings, conclusions and recommendations in this paper are those of the authors and do not necessarily reflect the views of the funding agencies. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment. Proceedings of the 31st VLDB Conference, Trondheim, Norway, 2005 set of skyline groups and, for each subspace, the set of objects that are in the subspace sky- line. A performance study is reported to eval- uate our approach. 1 Introduction It has been well recognized that the skyline opera- tor is important for multi-criteria decision making ap- plications. A (classic) illustrative example of skyline queries is to search for hotels in Nassau (Bahamas) which are cheap and close to the beach [2]. Suppose each hotel has two attributes: the price and the dis- tance to the beach. Hotel A dominates hotel B (or, A is a better choice than B in the context of this exam- ple) if...
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p253-pei - Catching the Best Views of Skyline: A Semantic...

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